@gneubig: SkillsBench is a great benchmark, and I'm not just saying that because @OpenHandsDev beats everyone else on it Skills a…
Summary
SkillsBench 1.1 is a benchmark for evaluating AI agents' ability to use skills, now fully audited and error-free.
View Cached Full Text
Cached at: 06/18/26, 06:04 AM
SkillsBench is a great benchmark, and I’m not just saying that because @OpenHandsDev beats everyone else on it 😀
Skills are now the defacto standard for how we customize agents, so figuring out models/agents ability to use them well is super-important.
Xiangyi Li (@xdotli): A big pain point in using AI benchmarks is encountering errors after its first release. Today, we’re releasing SkillsBench 1.1, the first benchmark for how well AI agents use skills, now audited end to end and verified error-free. Prof. @dawnsongtweets joins 1.1 as advising
Similar Articles
@xdotli: A big pain point in using AI benchmarks is encountering errors after its first release. Today, we're releasing SkillsBe…
SkillsBench 1.1 is released as the first audited, error-free benchmark for AI agent skills, showing rapid capability improvement from ~36% to 67% resolution rate and demonstrating that skills can substitute for model scale.
FinSkillBench: Evaluating AI Agents and Domain Skills for Investment Management
FinSkillBench is an evaluation suite for AI agents in investment management, showing that curated procedural skills improve performance compared to self-generated skills.
SkillLearnBench: Benchmarking Continual Learning Methods for Agent Skill Generation on Real-World Tasks
SkillLearnBench introduces the first benchmark for evaluating continual skill learning in LLM agents across 20 real-world tasks, revealing that no method dominates and scaling LLMs does not guarantee better skills.
SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills
SkillEvolBench is a diagnostic benchmark for evaluating whether large language model agents can distill episodic experience into reusable procedural skills. It includes 180 tasks across six environments and finds that current agents often struggle to form robust reusable skills, with raw trajectory reuse often outperforming distilled skills.
SkillEvaluator is coming to ClawHub
SkillEvaluator, an open-source tool for evaluating AI agent skills, is being integrated into ClawHub by Patrick with NVIDIA's support, providing quantitative benchmarks to help users find skills that improve agent performance.